Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+import json
+from difflib import SequenceMatcher
+
+# Load pre-trained speech-to-text model
+recognizer = pipeline("automatic-speech-recognition")
+
+# Load Qur'an verses from JSON file
+with open('quran_verses.json', 'r', encoding='utf-8') as f:
+    quran_verses = json.load(f)["verses"]
+
+# Load user progress
+try:
+    with open('user_progress.json', 'r', encoding='utf-8') as f:
+        user_progress = json.load(f)
+except FileNotFoundError:
+    user_progress = {"memorized_verses": []}
+
+# Function to calculate the similarity between two texts
+def calculate_similarity(a, b):
+    return SequenceMatcher(None, a, b).ratio()
+
+# Function to update user progress
+def update_progress(verse):
+    if verse not in user_progress["memorized_verses"]:
+        user_progress["memorized_verses"].append(verse)
+        with open('user_progress.json', 'w', encoding='utf-8') as f:
+            json.dump(user_progress, f, indent=4)
+
+# Function to calculate progress percentage
+def calculate_progress():
+    total_verses = len(quran_verses)
+    memorized_verses = len(user_progress["memorized_verses"])
+    return (memorized_verses / total_verses) * 100
+
+# Function to provide detailed feedback based on similarity score
+def get_feedback(similarity):
+    if similarity > 0.9:
+        return "Excellent! Your recitation is almost perfect!"
+    elif similarity > 0.75:
+        return "Good job! You’re getting close, but there’s room for improvement."
+    elif similarity > 0.5:
+        return "Not bad, but practice some more to improve accuracy."
+    else:
+        return "Keep practicing, and try again!"
+
+# Function to process audio and match it with the closest Qur'an verse
+def process_audio(audio):
+    transcription = recognizer(audio)["text"]
+    
+    # Find the most similar verse
+    most_similar_verse = None
+    highest_similarity = 0
+    for verse in quran_verses:
+        similarity = calculate_similarity(transcription, verse["text"])
+        if similarity > highest_similarity:
+            highest_similarity = similarity
+            most_similar_verse = verse
+
+    # Update progress if the match is good enough
+    if most_similar_verse and highest_similarity > 0.8:  # Threshold of 80% similarity
+        update_progress(most_similar_verse)
+        progress = calculate_progress()
+        feedback = get_feedback(highest_similarity)
+        return (
+            f"Transcription: {transcription}\n"
+            f"Closest verse: {most_similar_verse['text']}\n"
+            f"Similarity: {highest_similarity * 100:.2f}%\n"
+            f"Feedback: {feedback}\n"
+            f"Progress: {progress:.2f}%"
+        ), progress / 100  # Return progress as a decimal for the progress bar
+    else:
+        return (
+            f"Transcription: {transcription}\n"
+            f"No matching verse found or similarity too low.\n"
+            f"Progress: {calculate_progress():.2f}%"
+        ), calculate_progress() / 100  # Return progress as a decimal for the progress bar
+
+# Interface
+iface = gr.Interface(
+    fn=process_audio, 
+    inputs=gr.Audio(source="microphone", type="filepath"), 
+    outputs=[gr.Textbox(), gr.Progress(label="Memorization Progress")],
+    title="Qur'an Memorization Helper",
+    description="Speak a verse, and we'll transcribe it, check your accuracy, and track your progress."
+)
+
+# Launch the app
+iface.launch()